1. Field of the Invention
The present invention relates to a motion correction device for a camcorder (camera recorder), and more particularly, to the one-dimensional image component pick-up unit for correcting an unstable image from a camcorder caused by unsteady hands.
2. Description of the Related Art
Detection of a motion vector from a dynamic image signal is an essential technique in the compression, recognition, stabilization, etc. of an image. When a portable video camera is used in conjunction with a VCR (videocassette recorder) to take a picture, an image input to the camera is likely to be unstable and shaking, especially when the user is walking or in a moving vehicle. A common problem of camcorders is that when a picture is highly magnified, the instability caused by unstable hands is more pronounced.
A solid state pick-up unit is widely used as an input device of a camcorder. The solid state pick-up unit is a two-dimensional image pick-up unit made from a semiconductor chip which does not use electron beams. There are two types of solid state pick-up unitsxe2x80x94a MOS type which uses a metal oxide semiconductor (MOS) transistor in a light receiver, and a CCD (charge coupled device) type.
In the following, an existing image correction system will be explained in conjunction with the accompanying drawings. FIG. 1 is a block diagram showing a conventional image correction system, and FIG. 2 is a conceptual diagram showing a conventional method of detecting a motion vector for an image by detecting a pair of one-dimensional vector components.
As shown in FIG. 1, the conventional image correction system for stabilizing an image comprises a CCD imager 11 (a solid state pick-up unit) which picks up an input image from incident light that has passed through an optical system, scans the image electronically within the solid state device, and converts the image into electrical signals. An analog/digital converter 12 (referred to as an AID converter hereinafter) converts the analog signals output from the CCD imager 11 into digital signals. A camera signal processing unit 13 converts a signal output from the A/D converter into color and brightness signals. A motion vector detecting unit 14 computes a motion vector from the signal output from the A/D converter 12. A memory control unit 15 receives the motion vector output from the motion vector detecting unit 14 to control the position of pixels in the image. A field memory 16 holds a field unit (or a frame unit) of color and brightness data from the camera signal processing unit 13 and, under the control of the memory control unit 15, outputs a stabilized image signal. A digital/analog converter 17 (referred to as a D/A converter hereinafter) converts the corrected color/brightness signals from the field memory 16 into an analog image signal to be recorded.
In such an image correction system, covariance values are calculated between image data selected from two sequential images, and a motion vector is determined based on the point where the minimum covariance value occurs.
In general, a block matching algorithm is used to calculate the covariance value. Performance of the motion vector correction is impaired for the time it takes to apply the block matching algorithm. In order to completely calculate the correction under the constraints of real-time processing, it has been suggested that various techniques be used, such as pyramid searching, logarithmic searching, and so on. A two-dimensional block matching algorithm, however, entails a rapid increase in the number of arithmetic operations with an increase in the number of pixels to be considered. Furthermore, when a subset of pixels from the image is considered, the block matching algorithm is likely to produce erroneous results such as detecting a motion correction vector at a local minimum, which stabilizes only a portion of the image.
As shown in FIGS. 2(A) and 2(B), a general method has also been used which extracts one-dimensional components of the motion correction vector by projecting the image pattern onto a horizontal axis and a vertical axis, and computing the horizontal and vertical components of the correction vector separately.
After an image pattern has been projected in the directions of the horizontal and vertical axes, the projected result is compared with the projected result of the preceding image pattern to calculate one-dimensional covariance values. A displacement quantity between the two fields is determined from the point where the minimum covariance value results. Let an x and y coordinate system represent horizontal and vertical axes, respectively, of an image. Assuming that M is the number of horizontal pixels in each line of an image, and that N is the number of lines of an image, the horizontal covariance value, for example, can be calculated by an equation such as the following:                               C          ⁡                      (            u            )                          =                              ∑                          x              =              S                                      M              -              S                                ⁢                      "LeftBracketingBar"                                                            P                  h                  xe2x80x2                                ⁡                                  (                                      x                    +                    u                                    )                                            -                                                P                  h                                ⁡                                  (                  x                  )                                                      "RightBracketingBar"                                              (        1        )            
where Phxe2x80x2 and Ph are line memories into which the preceding and the present image horizontal component data are accumulated, respectively. The variable u {u|xe2x88x92S less than u less than S} is an integer within a searching distance xc2x1S, and it represents a displacement variable as a number of pixels. If a value of the variable u results in the minimum value of C(u), that value of u is considered to be the optimum horizontal displacement of an image. A similar computation is done for the vertical component. Compared with a two-dimensional matching algorithm, a one-dimensional signal matching algorithm applied to each of two axes x and y enables the calculation of a motion vector using fewer arithmetic operations, even when there is a large displacement between images.
The one-dimensional signal matching algorithm, however, also has a time restraint. The calculation of covariance should be finished before the raster scanning of the next field begins, yet the projection of the present field image data can not be completed until the raster scanning of a previous input image comes to an end. Further, an input pixel should be converted into a low quantified level (a binary signal, etc.) in order to economize on the memory used to accumulate the projection. Also, the determination of a threshold value in the conversion of pixels into a binary signal and the extraction of contours of an image, can lead to the loss of some pixel data. In addition, two pairs of line memories are required, of which one pair has N registers, the number of lines of an input image, and the other pair has M, the number of horizontal pixels. Finally, a complete one-dimensional signal matching algorithm must be implemented in the circuitry.
In order to solve the above-mentioned problems, Korean Patent Application No. 95-27157 has disclosed a device and method for detecting a motion vector of a camcorder. Besides a main CCD, the disclosed device uses separate image pick-up units to obtain one-dimensional component data at a high speed, uses a pipeline processing method to enable the rapid calculation of covariance values between successive image component data, and uses fewer line memories to allow for simpler circuitry.
FIG. 3 is a drawing which shows the principles of picking up an image through an image pick-up unit according to a conventional embodiment. FIG. 4 is a drawing which shows horizontal and vertical image component pick-up units and peripheral units thereof.
As shown in FIG. 3, a conventional image pick-up unit 30 includes two right-angled prisms 31 and 32, the hypotenuses of which are joined to each other to form a reflection surface that can reflect an incident two-dimensional image. A plano convex lens 33 has a flat surface which faces the reflection surface of the two right-angled prisms 31 and 32, and condenses the reflected image into a one-dimensional image component. A line CCD 34 converts the one-dimensional image component into electrical signals.
The basic principle of picking up an image is to reflect a two-dimensional image horizontally or vertically by two prisms 31 and 32, to condense the reflected two-dimensional image into a one-dimensional image through the plano convex lens 33, and to pick-up the one-dimensional image component in the line CCD 34.
As shown in FIG. 4, a horizontal/vertical pick-up unit 40 is made up of two image component pick-up units. A horizontal component pick-up unit, made up of a horizontal pair of prisms 41 and 42, a horizontal plano convex lens 43, and a horizontal line CCD 44, receives a two-dimensional image and outputs horizontal component data. A vertical component pick-up unit, made up of a vertical pair of prisms 45 and 46, a vertical piano convex lens 47, and a vertical line CCD 48, receives a two-dimensional image and outputs vertical component data.
There is an orientation difference of 90xc2x0 between the horizontal component pick-up unit (41, 42, 43 and 44), and the vertical component pick-up unit (45, 46, 47 and 48). As shown in FIG. 4, the horizontal/vertical image pick-up unit 40 reflects light input from a camera lens vertically and horizontally through corresponding right-angled prisms pairs 41, 42 and 45, 46, respectively. The vertically reflected image and the horizontally reflected image are condensed through corresponding piano convex lenses 43 and 47, respectively, and finally converted into electrical signals in horizontal and vertical line CCDs 44 and 48, respectively.
Assuming that an input image is picked up by both the horizontal line CCD 44 and the vertical line CCD 48, and that the length (number of registers) of the horizontal line CCD 44 is M, and the length of the vertical line CCD 48 is N, the resultant image components can be represented by the following equations:                                           P            h                    ⁡                      (            x            )                          =                  α          ⁢                                    ∑                              y                =                0                                            N                -                1                                      ⁢                          I              ⁡                              (                                  x                  ,                  y                                )                                                                        (        2        )                                                      P            v                    ⁡                      (            y            )                          =                  α          ⁢                                    ∑                              x                =                0                                            M                -                1                                      ⁢                          I              ⁡                              (                                  x                  ,                  y                                )                                                                        (        3        )            
where, (x, y) are the coordinates of a pixel from the image, I (x, y) is the brightness of the pixel, and Ph and Pv are the vertically and horizontally condensed components, respectively. The variable xcex1 is a reflection coefficient for light incident upon the reflection surface of the pair of prisms. The horizontal and vertical component images, which have been linearly condensed, are converted into electrical signals in the horizontal and vertical line CCDs 44 and 48, respectively, and are output to circuits for detecting motion vectors.
The conventional image component pick-up unit just described still faces problems such as a complicated construction and a large size. Accordingly, a need exists for an image component pick-up unit which overcomes the above-mentioned problems.
The present invention has been made in an effort to solve one or more of the problems with the conventional motion correction devices, including those mentioned above. To provide a simple construction and small-sized pick-up unit, thin transmitter-reflectors are used instead of a pair of right angle prisms.
To achieve these and other advantages, the present invention provides for a motion correction device, for images recorded from incident light having an incident direction, comprising at least one of horizontal and vertical component pick-ups, each component pick-up comprising a converter for converting light into electrical signals, and a thin transmitter-reflector for transmitting a portion of the incident light at substantially the incident direction and for reflecting a remaining portion of the incident light at a range of other directions such that substantially all the reflected light impinges on the converter. In another aspect of the invention, a curved mirror is used as the thin transmitter-reflector.
In other aspects of the invention the motion correction device further comprises a condenser and uses a flat mirror as the thin transmitter-reflector.
In still other aspects of the invention, the motion correction device further comprises motion component detectors whereby a motion vector signal is defined, and a control means responsive to the motion vector signal for changing color/brightness signals.